Systems and methods for predicting functions based on multimodal data objects

Abstract

Systems, methods, and non-transitory computer readable mediums are provided herein for receiving one or more multimodal data objects associated with a subject entity and one or more interactions with an electronic device. The subject entity can include a software module, a digital asset, a system component, an individual, or the like. A multimodal data object is derived from analysis of at least video, audio, and textual data. A predictive function data object is generated based on multimodal data objects by a predictive function model. A predictive function data object is configured to predict how subject entity expressions impact one or more additional entities. One or more actions are performed based on the predictive function data object. An action performed can include reconfiguring a composition of one or more structural data objects, generating electronic communications, and the like. Electronic communications are provided in real-time and/or subsequent to an interactive session.

1 . A system comprising one or more processors, and memory having instructions that, when executed by the one or more processors, cause the one or more processors to:
 receive one or more multimodal data objects associated with a subject entity and one or more interactions with an electronic device;   generate, by applying the one or more multimodal data objects to a predictive function model, a predictive function data object associated with at least the subject entity; and   perform one or more actions based on the predictive function data object.   
     
     
         2 . The system of  claim 1 , wherein the one or more multimodal data objects are associated with a respective one or more event markers, and wherein the instructions that, when executed by the one or more processors, further cause the one or more processors to:
 update the predictive function model by applying a sequence of multimodal data objects having respective one or more event markers.   
     
     
         3 . The system of  claim 1 , wherein the one or more multimodal data objects are further associated with one or more additional entities, and wherein the predictive function data object is further associated with the one or more additional entities. 
     
     
         4 . The system of  claim 3 , wherein the predictive function data object is associated with inter-related functions of a plurality of entities. 
     
     
         5 . The system of  claim 1 , wherein the one or more multimodal data objects are derived from one or more of electronic mail messages, short message service (SMS) texts, video data, rich communication services (RCS), electronic images, instant message data, chat data, virtual meeting interaction data, audio data, or online communication vehicles. 
     
     
         6 . The system of  claim 1 , wherein the instructions that, when executed by the one or more processors, further cause the one or more processors to:
 receive one or more annotated multimodal data objects;   generate the predictive function model based on the one or more annotated multimodal data objects; and   update the predictive function model based on one or more training parameters.   
     
     
         7 . The system of  claim 1 , wherein the predictive function data object is associated with one or more of a charismatic leadership feature, an ethical leadership feature, a transformational leadership feature, a shared leadership feature, a transactional leadership feature, an authentic leadership feature, a destructive leadership feature, an effective leadership feature, or a supportive followership feature. 
     
     
         8 . The system of  claim 1 , wherein the predictive function model comprises a large language model. 
     
     
         9 . The system of  claim 1 , wherein performing one or more actions based on the predictive function data object comprises:
 generating one or more subject entity performance interface components; and   causing rendering of the one or more subject entity performance interface components via a display device of the electronic device associated with the subject entity.   
     
     
         10 . The system of  claim 1 , wherein performing one or more actions based on the predictive function data object comprises:
 generating an electronic communication indicating at least one of one or more subject entity behavior improvement features, or a team composition feature.   
     
     
         11 . The system of  claim 1 , wherein performing one or more actions based on the predictive function data object comprises:
 reconfiguring a composition of one or more structural data objects.   
     
     
         12 . The system of  claim 10 , wherein the instructions that, when executed by the one or more processors, further cause the one or more processors to:
 cause rendering of the electronic communication via a display device of the electronic device associated with the subject entity in real time during a virtual meeting.   
     
     
         13 . The system of  claim 1 , wherein the instructions that, when executed by the one or more processors, further cause the one or more processors to:
 receive one or more additional multimodal data objects associated with a subject entity and one or more interactions with an electronic device;   generate, by applying the one or more additional multimodal data objects to the predictive function model, a subject entity profile associated with at least the subject entity;   generate, based on the subject entity profile, an electronic communication configured for display via a display device; and   transmit the electronic communication to the electronic device associated with the subject entity.   
     
     
         14 . A computer-implemented method comprising:
 receiving one or more multimodal data objects associated with a subject entity and one or more interactions with an electronic device;   generating, by applying the one or more multimodal data objects to a predictive function model, a predictive function data object associated with at least the subject entity; and   perform one or more actions based on the predictive function data object.   
     
     
         15 . The computer-implemented method of  claim 14 , wherein the one or more multimodal data objects are associated with a respective one or more event markers, further comprising:
 updating the predictive function model by applying a sequence of multimodal data objects having respective one or more event markers.   
     
     
         16 . The computer-implemented method of  claim 14 , wherein the one or more multimodal data objects are further associated with one or more additional entities, and wherein the predictive function data object is further associated with the one or more additional entities. 
     
     
         17 . The computer-implemented method of  claim 14 , wherein the one or more multimodal data objects are derived from one or more of electronic mail messages, short message service (SMS) texts, video data, rich communication services (RCS), electronic images, instant message data, chat data, virtual meeting interaction data, audio data, or online communication vehicles. 
     
     
         18 . The computer-implemented method of  claim 14 , further comprising:
 receiving one or more annotated multimodal data objects;   generating the predictive function model based on the one or more annotated multimodal data objects; and   updating the predictive function model based on one or more training parameters.   
     
     
         19 . The computer-implemented method of  claim 14 , wherein performing one or more actions based on the predictive function data object comprises:
 generating an electronic communication indicating at least one of one or more subject entity behavior improvement features, or a team composition feature.   
     
     
         20 . A non-transitory computer readable medium having instructions that, when executed by one or more processors, cause the one or more processors to:
 receive one or more multimodal data objects associated with a subject entity and one or more interactions with an electronic device;   generate, by applying the one or more multimodal data objects to a predictive function model, a predictive function data object associated with at least the subject entity; and   perform one or more actions based on the predictive function data object.